谷歌浏览器插件
订阅小程序
在清言上使用

Cognitive Performance and the Course of Depressive Symptoms over 7 Years of Follow-Up: the SMART-MR Study.

Psychological medicine(2014)

引用 6|浏览7
暂无评分
摘要
BackgroundDepressive symptoms and cognitive impairment often co-occur, but their interactive relationship is complex and the direction of causation is still a topic of research. We examined the influence of cognitive performance on the course of depressive symptoms during 7 years of follow-up in patients with vascular disease.MethodWithin the SMART-MR study, 736 patients (mean age 62 ± 10 years) had neuropsychological assessment on four cognitive domains at baseline [memory (MEM), working memory (WMEM), executive functioning (EXEC), and information processing speed (SPEED)]. Depressive symptoms were assessed with the Patient Health Questionnaire-9 (PHQ-9) at baseline and every 6 months during 7 years of follow-up. Generalized Estimating Equation (GEE) models were used to assess the association between cognitive performance with depressive symptoms at multiple time points during follow-up. Interaction terms between the respective cognitive domains and time was included to examine if the course of depressive symptoms differed according to baseline cognitive performance.ResultsThe GEE analyses showed no significant interactions between the respective cognitive domains and time indicating no different course of depressive symptoms according to baseline cognitive performance. Lower MEM, EXEC or SPEED, but not WMEM performance, was significantly associated with more depressive symptoms during follow-up per z score decrease: MEM [B = 0.70, 95% confidence interval (CI) 0.35–1.05]; EXEC (B = 0.88, 95% CI 0.41–1.36), and SPEED (B = 0.57, 95% CI 0.21–0.92).ConclusionsPoorer cognitive performance on the domains MEM, EXEC and SPEED, but not WMEM, was associated with higher levels of depressive symptoms over 7 years of follow-up, but not with a different course of depressive symptoms over time.
更多
查看译文
关键词
Atherosclerotic,cognition,depression,epidemiology,longitudinal
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要